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textonic: Interactive visualization for exploration and discovery of very large text collections

INFORMATION visualization 2019年第3期18卷 339-356页

作者： Paul, Celeste Lyn Chang, Jessica Endert, Alex Cramer, Nick Gillen, David Hampton, Shawn Burtner, Russ Perko, Ralph Cook, Kristin A. US Dept Def Laurel MD USA Georgia Inst Technol Atlanta GA 30332 USA Pacific Northwest Natl Lab Richland WA 99352 USA

textonic is a visual analytic system for interactive exploration of very large unstructured text collections. textonic visualizes hierarchical clusters of representative terms, snippets, and documents in a single, multi-scale spatial layout. Exploration is supported by interacting with the visualization and directly manipulating the terms in the visualization using semantic interactions. These semantic interactions steer the underlying analytic model by translating user interactions within the visualization to contextual updates to the supporting data model. The combination of semantic interactions and information visualization at multiple levels of the data hierarchy helps users manage information overload so that they can more effectively explore very large text collections. In this article, we describe textonic's data processing and analytic pipeline, user interface and interaction design principles, and results of a user study conducted mid-development with experienced data analysts. We also discuss the implications textonic could have on visual exploration and discovery tasks.

关键词： text and document visualization interactive visual analysis geospatial visualization adaptive user interfaces user study

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Interactive visual exploration of a large spatio-temporal dataset: Reflections on a geovisualization mashup

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IEEE TRANSACTIONS ON visualization AND COMPUTER GRAPHICS 2007年第6期13卷 1176-1183页

作者： Wood, Jo Dykes, Jason Slingsby, Aidan Clarke, Keith City Univ London Dept Informat Sci London England Univ Calif Santa Barbara Dept Geog Santa Barbara CA 93106 USA

Exploratory visual analysis is useful for the preliminary investigation of large structured, multifaceted spatio-temporal datasets. This process requires the selection and aggregation of records by time, space and attribute, the ability to transform data and the flexibility to apply appropriate visual encodings and interactions. We propose an approach inspired by geographical 'mashups' in which freely-available functionality and data are loosely but flexibly combined using de facto exchange standards. Our case study combines MySQL, PHP and the LandSerf GIS to allow Google Earth to be used for visual synthesis and interaction with encodings described in KML. This approach is applied to the exploration of a log of 1.42 million requests made of a mobile directory service. Novel combinations of interaction and visual encoding are developed including spatial 'tag clouds', 'tag maps', 'data dials' and multi-scale density surfaces. Four aspects of the approach are informally evaluated: the visual encodings employed, their success in the visual exploration of the clataset, the specific tools used and the 'rnashup' approach. Preliminary findings will be beneficial to others considering using mashups for visualization. The specific techniques developed may be more widely applied to offer insights into the structure of multifarious spatio-temporal data of the type explored here.

关键词： large dataset visualization text and document visualization multiresolution visualization geographic visualization applications of infovis

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Spatial analysis of news sources

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IEEE TRANSACTIONS ON visualization AND COMPUTER GRAPHICS 2006年第5期12卷 765-771页

作者： Mehler, Andrew Bao, Yunfan Li, Xin Wang, Yue Skiena, Steven SUNY Stony Brook Dept Comp Sci Stony Brook NY 11794 USA

People in different places talk about different things. This interest distribution is reflected by the newspaper articles circulated in a particular area. We use data from our large-scale newspaper analysis system (Lydia) to make entity datamaps, a spatial visualization of the interest in a given named entity. Our goal is to identify entities which display regional biases. We develop a model of estimating the frequency of reference of an entity in any given city from the reference frequency centered in surrounding cities, and techniques for evaluating the spatial significance of this distribution.

关键词： GIS geographic visualization text and document visualization information analytics WWW data visualization spidering newspapers

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Visualizing unstructured text sequences using iterative visual clustering

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9th International Conference on Visual Information Systems

作者： You, Qian Fang, Shiaofen Ebright, Patricia Indiana Univ Purdue Univ Dept Comp & Informat Sci 723 W Michigan StSL 280 Indianapolis IN 46202 USA Indiana Univ Dept Adult Hlth Sch Nursing Indianapolis IN 46202 USA

ISBN: (纸本)9783540764137

This paper presents a keyword-based information visualization technique for unstructured text sequences. The text sequence data comes from nursing narratives records, which are mostly text fragments with incomplete and unreliable grammatical structures. Proper visualization of such text sequences can reveal patterns and trend information rooted in the text records, and has significant applications in many fields such as medical informatics and text mining. In this paper, an Iterative Visual Clustering (IVC) technique is developed to facilitate multi-scale visualization, and at the same time provide abstraction and knowledge discovery functionalities at the visualization level. Interactive visualization and user feedbacks are used to iteratively group keywords to form higher level concepts and keyword clusters, which are then feedback to the visualization process for evaluation and pattern discovery. Distribution curves of keywords and their clusters are visualized at various scales under Gaussian smoothing to search for meaningful patterns and concepts.

关键词： text and document visualization nursing data processing

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Spatial analysis of news sources

Spatial analysis of news sources

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IEEE visualization Conference (Vis 2006)/IEEE Symposium on Information visualization (InfoVis 2006)

作者： Mehler, Andrew Bao, Yunfan Li, Xin Wang, Yue Skiena, Steven SUNY Stony Brook Dept Comp Sci Stony Brook NY 11794 USA

关键词： GIS geographic visualization text and document visualization information analytics WWW data visualization spidering newspapers

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BiblioViz: a system for visualizing bibliography information 06

BiblioViz: a system for visualizing bibliography information

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Proceedings of the 2006 Asia-Pacific Symposium on Information Visualisation - Volume 60

作者： Zeqian Shen Michael Ogawa Soon Tee Teoh Kwan-Liu Ma Computer Science Department University of California Davis Department of Computer Science San Jose State University

ISBN: (纸本)9781920682415

The InfoVis 2004 contest led to the development of several bibliography visualization systems. Even though each of these systems offers some unique views of the bibliography data, there is no single best system offering all the desired views. We have thus studied how to consolidate the desirable functionalities of these systems into a cohesive design. We have also designed a few novel visualization methods. This paper presents our findings and creation: BiblioViz, a bibliography visualization system that gives the maximum number of views of the data using a minimum number of visualization constructs in a unified fashion.

关键词： tables text and document visualization bibliography visualization applications of visualization graph visualization linked views

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HiPP: A Novel Hierarchical Point Placement Strategy and its Application to the Exploration of document Collections

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IEEE TRANSACTIONS ON visualization AND COMPUTER GRAPHICS 2008年第6期14卷 1229-1236页

作者： Paulovich, Fernando V. Minghim, Rosane Univ Sao Paulo ICMC Sao Paulo Brazil

Point placement strategies aim at mapping data points represented in higher dimensions to bi-dimensional spaces and are frequently used to visualize relationships amongst data instances. They have been valuable tools for analysis and exploration of data sets of various kinds. Many conventional techniques, however, do not behave well when the number of dimensions is high, such as in the case of documents collections. Later approaches handle that shortcoming, but may cause too much clutter to allow flexible exploration to take place. In this work we present a novel hierarchical point placement technique that is capable of dealing with these problems. While good grouping and separation of data with high similarity is maintained without increasing computation cost, its hierarchical structure lends itself both to exploration in various levels of detail and to handling data in subsets, improving analysis capability and also allowing manipulation of larger data sets.

关键词： text and document visualization hierarchical multidimensional visualization visual knowledge discovery high-dimensional data

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visualization of unstructured text sequences of nursing narratives 06

Visualization of unstructured text sequences of nursing narr...

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Proceedings of the 2006 ACM symposium on Applied computing

作者： Shiaofen Fang Min Lwin Patricia Ebright Indiana University-Purdue University Indianapolis Indianapolis IN Indiana University Middle Drive NU Indianapolis IN

ISBN: (纸本)9781595931085

This paper presents a keyword-based information visualization technique for nursing record sequences. Visualizing the trend information rooted in unstructured and fragmented abstract text data is a largely unaddressed problem. In our technique, multiple hierarchical keyword based visualizations are used to explore unstructured text data from nursing records. First, each text data set is broken up into a list of keywords to enable the visualization of keyword occurrences over time and the relative distribution of keywords. A graphical user interface is provided to enable selection and classification of keywords. Users may select one or more data sets to compare, in addition to one or more groups of keywords to add to the visualization. Colors are used to distinguish quickly and easily between groups of keywords present in the visualization. At the second level of hierarchy, keywords for visualization are discovered through a predetermined automatic detection and scoring based mechanism. The aggregate frequency trend of keywords from all data sets is also provided in both hierarchies as a way to visualize overall trends and analyze various events in time.

关键词： text and document visualization nursing data processing

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